Workforce sentiment monitoring and detection systems and methods

ABSTRACT

Exemplary implementations may provide a workforce sentiment and structure descriptions. A survey management tool can solicit and retrieve ratings data from employees via a survey. The received ratings can be aggregated and scaled according to employee ratings to identify and adjust for the impact of influential employees. An organizational chart may be updated based on the survey results and users may navigate the updated organizational chart to review employee ratings.

TECHNICAL FIELD

Embodiments of the present disclosure are generally related to systemsand methods for automatically determining and monitoring workplacecohesion.

BACKGROUND

Workplace cohesion can have an immediate and strong impact on workplaceproductivity. In many circumstances, it is difficult or impossible todetermine sentiment among employees of a workforce. For example,employees may be unwilling to truthfully share their impressions of eachother or it may be challenging to fully interview all employees within aworkplace, department, or working group. Where an employee does providefeedback relevant to workplace cohesion, it is often difficult todistinguish a “signal” within the “noise.” That is to say, the providedfeedback may be skewed by various latent biases of the employee. Whenworkplace cohesion cannot be determined, incompatible workers can beplaced on the same team, incompatible or inadequate management practicesmay continue unabated, and various other deteriorative phenomena withina workplace may occur due to a dissatisfied workforce.

In some cases, surveys may be distributed to employees in an attempt todetermine employee sentiment. However, distributing and processingsurveys adequately across a workforce to obtain a useful sample is oftenchallenging. While current survey methods track and aggregate feedbackamong all employees belonging to a department, age group, etc., nosurvey assigns ratings to individuals in the organization. In addition,interpreting individual coworker rating data can be difficult if notimpossible for a human as some employees may provide more useful datathan other employees due to employee personality, placement within thehierarchy of the company, level of interaction with co-workers, etc. Asa result, ratings applied to individual employees and also ratings ofother employees (i.e., co-workers) are most useful when interpretedwithin a context including all employee ratings within the workforce. Inorder to achieve said context, a way of distributing surveys, monitoringsurvey completion, interrelating survey results, processing surveyresults, and presenting the results in an intuitive and actionablemanner may be needed.

It is with these observations in mind, among others, that aspects of thepresent disclosure were concerned and developed.

SUMMARY

A method for determining employee sentiment ratings includes receivingratings data, the ratings data associated with one or more employees andresponsive to a survey, aggregating the ratings data to generateadjusted ratings for the one or more employees, generating a reportbased on the generated adjusted ratings, and generating a navigableinterface including the generated report, the navigable interfaceaccessible to an authorized user.

The method may further include receiving an organizational (org) chart,visually associating one or more portions of the org chart with thegenerated adjusted ratings, and wherein the generated navigableinterface further includes the org chart.

The method may further include receiving survey parameters, the surveyparameters identifying the one or more employees to survey, identifyinga mismatch between the org chart and the identified one or moreparameters, the mismatch including one of an employee not included inthe org chart or an employee of the org chart not included among theidentified one or more employees, and prompting the authorized user tospecify a reason for the mismatch.

The method may further include generating respective scores for each ofthe one or more employees, each respective score based on one or more ofratings received from coworkers organizationally above a respectiveemployee of the one or more employees, ratings received from coworkersorganizationally below the respective employee, ratings received fromcoworkers within a shared department of the respective employee, orratings received from coworkers in different departments than that ofthe respective employee, and categorizing the one or more employeesbased on the respective scores, wherein the navigable interface furtherincludes one of the respective scores or the categorized one or moreemployees.

The method may further include grouping the adjusted ratings data intodepartment groups, aggregating the grouped adjusted ratings data basedon the department groups, and generating inter-departmental data basedon the aggregated grouped adjusted ratings data, wherein the navigableinterface further includes the inter-departmental data.

The method may further include generating a set of weight values for theone or more employees, the weight values corresponding to the ratingsdata associated with the one or more employees, and generating theadjusted ratings by weighting the ratings data according to the set ofweight values.

The method may further include generating a projected performance forthe one or more employees based on the adjusted ratings.

A system for determining employee sentiment ratings includes one or moreprocessors, and a memory including instructions for the one or moreprocessors to receive ratings data, the ratings data associated with oneor more employees and responsive to a survey, aggregate the ratings datato generate adjusted ratings for the one or more employees, generate areport based on the generated adjusted ratings, and generate a navigableinterface including the generated report, the navigable interfaceaccessible to an authorized user.

The system may further include instructions to receive an organizational(org) chart, visually associate one or more portions of the org chartwith the generated adjusted ratings, and wherein the generated navigableinterface further includes the org chart.

The system may further include instructions to receive surveyparameters, the survey parameters identifying the one or more employeesto survey, identify a mismatch between the org chart and the identifiedone or more parameters, the mismatch including one of an employee notincluded in the org chart or an employee of the org chart not includedamong the identified one or more employees, and prompt the authorizeduser to specify a reason for the mismatch.

The system may further include instructions to generate respectivescores for each of the one or more employees, each respective scorebased on one or more of ratings received from coworkers organizationallyabove a respective employee of the one or more employees, ratingsreceived from coworkers organizationally below the respective employee,ratings received from coworkers within a shared department of therespective employee, or ratings received from coworkers in differentdepartments than that of the respective employee, and categorize the oneor more employees based on the respective scores, wherein the navigableinterface further includes one of the respective scores or thecategorized one or more employees.

The system may further include instructions to group the adjustedratings data into department groups, aggregate the grouped adjustedratings data based on the department groups, and generateinter-departmental data based on the aggregated grouped adjusted ratingsdata, wherein the navigable interface further includes theinter-departmental data.

The system may further include instructions to generate a set of weightvalues for the one or more employees, the weight values corresponding tothe ratings data associated with the one or more employees, and generatethe adjusted ratings by weighting the ratings data according to the setof weight values.

The system may further include instructions to generate projectedperformance for the one or more employees based on the adjusted ratings.

A non-transitory computer readable medium storing instructions that,when executed by one or processors, cause the one or more processors toreceive ratings data, the ratings data associated with one or moreemployees, and responsive to a survey, aggregate the ratings data togenerate adjusted ratings for the one or more employees, generate areport based on the generated adjusted ratings, and generate a navigableinterface including the generated report, the navigable interfaceaccessible to an authorized user.

The non-transitory computer readable medium may further storeinstructions to receive an organizational (org) chart, visuallyassociate one or more portions of the org chart with the generatedadjusted ratings, and wherein the generated navigable interface furtherincludes the org chart.

The non-transitory computer readable medium may further storeinstructions to receive survey parameters, the survey parametersidentifying the one or more employees to survey, identify a mismatchbetween the org chart and the identified one or more parameters, themismatch including one of an employee not included in the org chart oran employee of the org chart not included among the identified one ormore employees, and prompt the authorized user to specify a reason forthe mismatch.

The non-transitory computer readable medium may further storeinstructions to generate respective scores for each of the one or moreemployees, each respective score based on one or more of ratingsreceived from coworkers organizationally above a respective employee ofthe one or more employees, ratings received from coworkersorganizationally below the respective employee, ratings received fromcoworkers within a shared department of the respective employee, orratings received from coworkers in different departments than that ofthe respective employee, and categorize the one or more employees basedon the respective scores, wherein the navigable interface furtherincludes one of the respective scores or the categorized one or moreemployees.

The non-transitory computer readable medium may further storeinstructions to group the adjusted ratings data into department groups,aggregate the grouped adjusted ratings data based on the departmentgroups, and generate inter-departmental data based on the aggregatedgrouped adjusted ratings data, wherein the navigable interface furtherincludes the inter-departmental data.

The non-transitory computer readable medium may further storeinstructions to generate a set of weight values for the one or moreemployees, the weight values corresponding to the ratings dataassociated with the one or more employees, generate the adjusted ratingsby weighting the ratings data according to the set of weight values, andgenerate a projected performance for the one or more employees based onthe adjusted ratings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a system architecture for monitoring and detectingemployee sentiment, according to embodiments of the present technology;

FIG. 2 illustrates a flowchart for a method for generating reports,according to embodiments of the present technology;

FIG. 3 illustrates a flowchart for a method for generating aggregatedratings for employees, according to embodiments of the presenttechnology;

FIG. 4 illustrates a flowchart for a method for adjusting employeeratings, according to embodiments of the present technology;

FIG. 5 illustrates an example survey, according to embodiments of thepresent technology;

FIG. 6 illustrates an example user interface, according to embodimentsof the present technology;

FIGS. 7A-B illustrate example reporting interfaces for departments,according to embodiments of the present technology;

FIG. 8 illustrates an example reporting interface for an individual andteam, according to embodiments of the present technology;

FIG. 9 illustrates an example reporting interface for a team, accordingto embodiments of the present technology;

FIG. 10 illustrates a flowchart for a method for associating survey datawith organizational chart information, according to embodiments of thepresent technology;

FIG. 11 illustrates an example system architecture, according toembodiments of the present technology; and

FIG. 12 illustrates an example computing system for performing methodsof the present disclosure, according to embodiments of the presenttechnology.

DETAILED DESCRIPTION

One aspect of the present disclosure relates to a cloud computing basedfeedback and rating system provided over a web interface enablingemployees to anonymously rate each other. As used in this disclosure,“employee” is understood to refer to any member of a workforce in anycapacity; “supervisor” is understood to refer to any employee under whomother employees work and/or to whom other employees report; and,“coworker” refers to other employees within the same workforce as areferenced employee. Each employee (e.g., including supervisors,managers, executives, associates, etc.) may be given a rating which canbe used to determine trends for each employee and/or aggregated trendsacross groups of employees (e.g., entire organization, department,workgroup, team, etc.).

Results of the determination may be displayed in an organizational chart(“org chart”) depicting a structure and population of each employeewithin a company. As a result, employee sentiment across theorganization can be ascertained, management is able to make informeddecisions regarding promotions, demotions, raises, firings, andperformance improvement plans, and Human Resources (HR) departments areable to quickly measure employee engagement across an entireorganization. These decisions are typically made at the sole discretionof each supervisor, without collecting feedback from all relevantcoworkers.

The employee sentiment, provided as actionable data via the displayedorg chart interface, may be used for downstream processes. For example,determination of raises, applying strikes to a record, identification ofcandidates needing coaching, documentation of causes for termination,and identification of employees meriting termination can be based on theactionable data.

A survey may be provided (e.g., automatically) to employees (e.g., as aunique link to a web application, etc.) and provide a data intake forgenerating actionable data analytics. The survey can be conducted oneither mobile or desktop devices. The data analytics may be as granularas a single employee or as aggregated as an entirety of the organization(e.g., company-wide), as well as by department, workgroup, team, etc.For example, if a company is divided into a sales division and anengineering division, and the engineering division is further dividedinto backend team and frontend team, then the analysis may be performedfor the whole company, the sales division, the overall engineeringdivision, the backend team of the engineering division, and/or thefrontend team of the engineering division.

An authorized user, such as an employer or the like, can log in to a webapplication and choose survey parameters. Survey parameters may include,for example and without imputing limitation, a survey start date,reporting frequency, survey availability duration, individual employeesto survey, employee groups (e.g., workgroup, team, division, department,etc.), etc.

The web application may generate an org chart based on a provided orgchart (e.g., by the company) and employee photographs. The authorizeduser can then visually explore the generated org chart to, for example,check for errors, etc. In some examples, where the generated org chartdoes not include employees from a previous survey, the authorized usermay be prompted to provide correction or explanation (e.g.,documentation) such as whether the respective employee retired, wasfired, quit, etc. The correction and/or explanation can then be used forfurther trend analysis.

Employees, either indicated by the survey parameters or across theentire company by default, may receive an email allowing each respectiveemployee to directly log into the web application and begin the survey.Employees may be asked overall company satisfaction questions and cansee a list of coworkers within the same department who they may rate. Insome examples, the employee may add additional coworkers to rate. As anemployee adds additional coworkers, that same employee may be added to alist provided to each additional coworker. In some examples, the listcan include the employee who rated the additional coworkers. In someexamples, this list may obfuscate which employees rated which otheremployees by adding a random subset or an entire group or department toa list to be rated by a coworker based on the employee adding them.

A survey may be visible to different groups of users depending on itsstate. For example, the survey may be in “Pending” state after it hasbeen configured and scheduled by an administrator, but is not yet openfor responses. In the Pending state, the survey may be only visible toadministrators. Once the administrator opens the survey, either bymanually triggering it to be opened or by setting a timer for when thesurvey should open, the survey enters an “Open” state. In the Openstate, all users may access and update their responses to the survey.Once a user completes a survey, the survey may enter an “Admin Review”state, and the responses may be sent to an administrator for review. Ifthe administrator completes the review process and deems the surveyvalid, the survey then enters a “Closed” state and becomes available forall users to view. If the administrator considers the survey resultsinvalid, the administrator may delete the survey, and the survey entersa “Deleted” state such that only certain administrators (e.g., “super”administrators, etc.) may view the surveys. In some examples, a surveythat has been in the Closed state for a predetermined amount of time maybe automatically changed to be in the Deleted state.

Generally, the survey may visually indicate that, on average, employeesshould rate coworkers an average score. For example, where the surveyprovides a ranking of 1-5, the average may be a three and the three maybe located centrally along a sequence and/or be highlighted bydistinctive selection size, font format, coloration, etc. Or, in otherwords, the survey may visually indicate that a surveyed employee shouldon average rate coworkers targeting an average of three. Additionally,the survey can include for each rated coworker a list of selectableattributes that are descriptive of that coworker such as, for exampleand without imputing limitation, “angry”, “indecisive”, “friendly”,“creative”, “uncooperative”, “inflexible”, “communicator”, “reliable”,“vindictive”, “apathetic”, “enthusiastic” “hard-working”, “rude”,“disorganized”, “intelligent”, and “team-oriented”.

In some examples, the coworker ratings are based on how much an employee(responding to the survey) likes working with the respective coworker.The rating will typically be a combination of the friendliness of thecoworker, willingness to help, and ability to accomplish work (i.e., asperceived by the employee). However, each employee may determine theirown respective most important factors for each coworker to generate dataindicating which employees are most effective at raising companysatisfaction levels overall.

Additionally, employees, such as supervisors or managers, can view afull org chart during and after the survey via the web application. As aresult, employees may visualize and interactively explore the companystructure. While the survey is active, the employee can select coworkersto rate directly from the org chart. Further, as the survey progressesacross all selected employees, authorized users may view how many havecompleted the survey (e.g., as a ratio, percentage complete, totalsurveys completed, etc.). In some examples, the generated org chart canbe viewed by the authorized user and a percent of employees under eachmanager who have completed the survey can be viewed so that, forexample, managers can be prompted to remind their employees to completethe survey.

The web application may include automated email processes associatedwith the survey. For example, while a survey is active for an employee,regular reminder emails may be sent to the employee prompting completionof the survey. Additionally, the employee may be sent an emailsoliciting a rating of additional coworkers identified by the system ascandidate coworkers the employee may want to rate. Various videotutorials and reminders (e.g., explaining anonymity, surveying process,results, interface, etc.) may be integrated directly into the webapplication.

Additionally, the web application may automatically identify eachemployee's interactions with customers. The web application will thenmessage the customers prompting them to complete a survey to providefeedback on the interactions. Results from these customer surveys maythen be collected and incorporated into the feedback and rating systemcorresponding to each employee.

Once the survey is complete, either due to all (e.g., a quorum) surveyedemployees completing the survey or as a result of the survey durationcompleting, actionable data analytics can be provided to, for example,senior leadership and HR. To protect privacy, data may be displayed onlywhere a respective sample size is five or more (e.g., n>=5). Forexample, if an employee has been rated by only a single coworker, dataregarding that employee may be withheld from being viewable. However,where an employee has been rated by five or more coworkers, a respectiveaverage rating and clustering of attributes selected for that employeemay be provided to HR. In some examples, the sample size threshold maybe different based on the type of data. For example, employee attributedata may have a threshold of 15 or more individual coworker ratings.Company-wide attributes and free comments may have a threshold of 100 ormore individual employee ratings (or company size, etc.).

The actionable data analytics can include a score for each employeebased on an aggregation of ratings that employee received through thesurvey. As part of the aggregation process, the ratings can be weighted,for example, based on the employee that provided them.

For example, every score may be initialized to a predetermined average(e.g., provided by the authorized user, etc.). For example, thepredetermined average may be 8.0. Each rating to be aggregated into thescore can be converted into a value of −1.0, −0.4, 0, +0.8, or +2.0 toresult in a final score between 7.0 and 10.0 for each employee. Theconverted ratings may then be summed, and a weight may be applied to thesummation based on the number of response. For example, and withoutimputing limitation, the table below may describe a weighting schemebased on n number of responses received.

TABLE 1 Responses Score Weight n = [1, 5] 0.3x n = [6, 10] 0.5x n = [11,20] 0.7x n = [21, 30] 0.8x n = [31, 50] 0.9x n > 50   1x

Further, where 50 or more coworkers all rate an employee, a minimumscore may be given to the employee (e.g., a converted value of −1.0).However, where 50 or more coworkers all rate an employee, a maximumscore can be given to the employee (e.g., a converted value of +2.0).

Once ratings have been determined, employees receiving a maximum rating(e.g., a rating of 10.0), may be associated with an increased weight(e.g., a factor of 1×) for rating given by that employee to coworkers.In comparison, employees receiving a minimum rating (e.g., a rating of7.0) may have their outgoing ratings reductively weighted (e.g., afactor of 0.25×). Employees between maximum and minimum ratings maylikewise receive weightings along a corresponding sliding scale. Toaccount for increased influence of employees substantially morewell-received within the company than average (and, likewise, accountfor decreased influence of employees substantially less well receivedwithin the company than average), outgoing ratings for each employee canbe recalculated based on the weighted values.

Other scores reflective of overall workforce trends can also becalculated. For example, a happiness score can be calculated based on ascale ranging from a “100%” indicating approximately 100% of employeesrating the company “5” on the survey to a “0%” indicating approximately100% of employees rating the company a “1”. Employee engagement can becalculated based on a percentage of users who responded to the surveyand/or rated the company a “4” or above. In some examples, companycomparisons can be conducted by the web application to provide insightas to, for example and without imputing limitation, engagement andhappiness scores of the company in comparison to other companies ofcomparable location, industry, size, etc. Further, the survey mayinclude plain text fields for employees to provide additional commentsand the like. The plain text results may be summarized with a list ofcomments and/or word cloud, which may limit the word/comment display togroups of more than 50 employee surveys to preserve anonymity, etc.

Survey results and actionable data analytics, such as the score and/orindividual ratings, can be provided to varying degree to defined groupswithin a company. For example, each employee can see anonymized ratingsand/or rating(s) over time as well as what attributes other employeeshave assigned to them. Employees may also see ratings received fromdifferent coworker groupings such as, for example and without imputinglimitation, coworkers above the employee (e.g., managers), coworkersbelow the employee (e.g., coworkers who report to the employee), insidecoworkers (e.g., coworkers within the same department as the employee),and outside coworkers (e.g., coworkers in different departments than theemployee), sometimes referred to as ABIO scores.

The ABIO scores can be used to automatically identify employee types andthe like. Generally, the employee types refer to a grouping of employeesby behavior such as personality, workstyle, performance, and/or otherfactors that may be useful for appraising an employee. For example, anemployee who has an “Above” rating averaging to 8.0 and “Below” and“Outside” ratings each respectively averaging out to 8.7 or higher maybe automatically labeled as a “Silent Superstar” because the extent ofthe employee contributions may not be fully known by those above them.

In some examples, an employee, such as a supervisor for example, canalso see the ratings of coworkers who report to that respective employee(e.g., members of a team for which the supervising employee isresponsible, etc.). Ratings for other coworkers (e.g., lateralsupervisors or managers hierarchically above the supervisor, etc.) maybe hidden from the employee. As a result, only a company chief executiveofficer (CEO) or equivalent may be able to view the ratings of everyemployee within the company.

The employee may view ratings of coworkers via the navigable org chartor by a list interface. The employee can automatically filter byemployee type when viewing coworker ratings. For example, a manager mayfilter by “Silent Superstar” to identify which employees are promisingand which supervisors may need additional coaching. In another example,an employee may filter according to overall high ratings or overall lowratings and the like. Additionally, an employee (e.g., a manager, etc.)can view a percentage indicating how many coworkers below them hascompleted the survey.

Further, based on the survey results and actionable data analytics, datacan be aggregated to automatically generate reports for particularemployee groups. In some examples, a rating can be generated for anentire department, which can be treated substantially similarly to anindividual employee (e.g., with ratings given by department members andratings received by individual department members and/or the departmentas a whole). Further, scaling factors (as discussed above) can beapplied or reapplied to the abstracted department and/or individual.

For example, department heads, HR, and administrators may receive areport including aggregated ratings indicating how each department likesworking with employees of other departments, internal employeesatisfaction levels as either a raw value or relative to otherdepartments, perception indicator of a selected department from otherdepartments either raw or relative to other departments, engagementlevel and completion rate of employees for each department, whichemployees work well with each department (e.g., a VP of an engineeringdepartment is rated very highly by more than 50 people in a purchasingdepartment, etc.), which employees work poorly with each department(e.g., a VP of a research and development department is rated poorly bymore than 20 people in an accounting department, etc.). Aggregatingindividual data into larger groups enables corporate issues to beidentified and addressed for department-wide cooperation levels.

In some examples, certain reports or report components may only beavailable to, for example, the CEO and/or designated HR representatives.For example, the certain reports or report components may include,without imputing limitation, a graph of average employee score, averagenumber of responses, and/or average happiness as a function of salary(e.g., in order to understand efficacy of the company at paying the mostliked employees higher salaries, etc.), an average overall companyratings for all employees, and ratings related to employees who havebeen fired, laid off, or have resigned (e.g., ratings of their managers,etc.).

These and other features, and characteristics of the present technology,as well as the methods of operation and functions of the relatedelements of structure, will become more apparent upon consideration ofthe following description and the appended claims with reference to theaccompanying drawings, all of which form a part of this specification,wherein like reference numerals designate corresponding parts in thevarious figures. It is to be expressly understood, however, that thedrawings are for the purpose of illustration and description only andare not intended as a definition of the limits of the invention. As usedin the specification and in the claims, the singular form of ‘a’, ‘an’,and ‘the’ include plural referents unless the context clearly dictatesotherwise.

FIG. 1 is an example system 100 for generating actionable data analyticsfrom an automated survey. System 100 may include one or more servers 102having an electronic storage 122 such as a database or other memorysystem and one or more processors 124 for performing machine-readableinstruction 106 to generate the actionable data analytics.

Machine-readable instructions 106 can include a variety of componentsfor performing specific actions or processes in performing automatedsurveys, managing the surveys, storing and processing data produced bythe surveys, and various other functions as may be apparent to a personhaving ordinary skill in the art. A survey management component 108 canperform, manage, and prepare a survey for users to respond to via clientcomputing platforms 104. Client computing platforms may receive and/orgenerate a user interface (UI) 105 for various operations such ascreating a survey, reviewing survey results, responding to a survey,etc.

A report generation component 110 may access survey results from surveymanagement 108 or from electronic storage 122 in order to generatereports which may be reviewed by users via client computing platforms104 or provided to external resources 120 (e.g., such as downstream APIsand the like). The external resources 120 may use the survey results,for example and without imputing limitation, to determine a probabilitythat an employee would perform well if promoted, or determine if anemployee is at high risk for disciplinary action. An org chartmanagement component 112 receives org charts from users and producesnavigable org charts associated with data from survey management 108,report generation 110, or electronic storage 122. Further, org chartmanagement 112 can update produced org charts according to surveymanagement 108 operations by, for example and without imputinglimitation, proposing optimizations to the org chart to improve teamstructure, or identifying new employees (e.g., new hires) or employeesthat are no longer surveyed (e.g., employee terminations/resignations).A scheduling service 114 may receive scheduling instructions from clientcomputing platforms 104 or external resources 120 and may enforcereceived schedules such as performing a survey at regular time intervalsor at specified times. An email service 116 can perform email operationssupporting the other components such as sending out survey notices,survey links, generated reports, org charts, and the like.

FIG. 2 is an example method 200 for generating reports based on andincluding actionable data analytics. Method 200 may be performed bysystem 100 to generate reports and the like.

At operation 202, survey parameters are received from an authorizeduser. Survey parameters may include designation of survey participantssuch as specific employees, departments, managers and/or those beneathdesignated managers, etc. Survey parameters may also include timing orscheduling information (e.g., to be processed by scheduling service 114)for performing a survey at specified times or a specified schedule. Insome examples, survey parameters can include specified survey questionsor formats.

At operation 204, a survey interface is generated based on the receivedparameters. The survey interface may be multiple pages long andstructured for scaling to computer, mobile, smartphone, and other deviceconstraints.

At operation 206, participants (e.g., designated in the surveyparameters) are provided access to the survey and can be prompted (e.g.,regularly, semi-regularly, scheduled, etc.) to complete the survey untilthe survey times out (e.g., expires according to a timing parameterprovided as a survey parameter). Participants may receive access to thesurvey via an email, link, text message, etc. provided by, for example,email service 116. For example, a link to the survey may be emailed toeach recipient and, when clicked, the link can direct the recipient to aweb application accessible via mobile, desktop, smartphone, and variousother devices.

At operation 208, the survey data provided by each participant isaggregated and processed into a report and provided to specifiedemployees (e.g., specified by the survey parameters). The generatedreport may be provided via email (e.g., by email service 116) and caninclude direct survey responses as well as generated data based on thesurvey responses such as, for example and without imputing limitation,happiness/satisfaction scores across the whole company, cohesioninformation, interdepartmental communications guidance, etc.

FIG. 3 is an example method 300 for processing survey response data. Insome examples, method 300 can be performed by survey component 108 andthe adjust scores can be used by report generation 110.

At operation 302, ratings are received for an employee (e.g., viasurvey) and a score can be set for the employee to a user definedaverage. The user defined average may be provided by an authorized uservia survey parameters during survey creation (e.g., as discussed abovein reference to FIG. 2).

At operation 304, each received rating for the employee is convertedinto a base value (e.g., −1.0, −0.4, 0, +0.8, +2.0 from a five starsystem). The converted values base values can be used to moreefficiently aggregate or otherwise process the ratings. For example, theconverted values may make aggregation methodologies involving summationeasier by placing values along a 0-100 and positive to negative scale.

At operation 306, the converted ratings are aggregated. In someexamples, aggregation can be accomplished via summation. In someexamples, aggregation can be performed according to certain algorithmsor averaging (e.g., mean, median, mode, etc.). At operation 308, theaggregated ratings are weighted (e.g., a multiplier is applied) based onhow many ratings were received.

FIG. 4 is a method 400 for processing ratings for an employee based onweighting considerations. For example, method 400 may be performed inorder to take into account company size and/or for varying influenceamong employees.

At operation 402, an aggregated rating is determined for an employee(e.g., via method 300 discussed above). The aggregated rating isdetermined based on surveyed coworkers of the employee and responserate.

At operation 404, ratings (e.g., of other employees, or coworkers) madeby the employee are adjusted according to a sliding scale based on therespective aggregated rating for said employee. For example, ratingsmade by an employee with a universally high rating may be weighted tocount for double when performing a respective aggregation process. Incomparison, ratings made by an employee with a universally minimalrating may be weighted to count for quarter as normal (e.g., weighted by0.25) when performing a respective aggregation process. Once adjustmentshave been made for every employee, at operation 406, each adjustedemployee ratings may be used to recalculate the employee ratings. As aresult, employee influence may be accounted for when performingaggregation of the survey data.

FIG. 5 is an example survey 500. Survey 500 can be performed by acomputer, mobile device, and/or smartphone. Survey 500 enables aresponder to provide satisfaction information related to a job,management, leadership, compensation, workspace, and the like.Additionally, free comments can be provided. Survey participants canalso rate coworkers based on a 1-5 rating of satisfaction working withthe respective coworker as well as selection of words from a descriptiveword bank.

FIG. 6 is an example user page 600 that can provide a user (e.g., anauthorized user), who may also be an employee, access to the systems andmethods of this disclosure. User page 600 can include a home page, orgchart page, reports page, and configuration page. The home page providesan overview of past, current, and planned surveys and includes links toresponse rate, results summary, detailed org charts, tabular formatteddata, and salary reports. Current surveys can be displayed withpercentage completed so far. Additionally, planned surveys may includelinks to survey settings (e.g., to provide or update survey parameters)as well as options to use a current org chart or update the org chart.

FIG. 7A is an example department report interface 700 that can provide auser (e.g., a manager, senior employee, etc.), a view of ratings whichhave been aggregated and abstracted to a particular department (e.g.,marketing, etc.) as a whole. Department report interface 700 can includean inter-department ratings section 710 and a department informationsection 720.

Inter-department ratings section 710 may include a tabular listing ofratings between other departments and the particular department.Further, a company-wide average rating, both rating the particulardepartment and as rated by the particular department, may be included atthe top of the tabular listing. In some examples, inter-departmentratings sections can provide a time-comparison view. Here, for example,inter-department ratings section 710 includes ratings for two differentyears (e.g., to appraise progress, etc.). In effect, inter-departmentratings section 710 enables a user to quickly view how otherdepartments, overall, interact with a particular department and soidentify which departments collaborate better or worse with each other.

Department information section 720 may include various departmentinformation to, for example, contextualize inter-department ratingssection 710 and the like. Depart information section 720 may include atabular view. In some examples, department information section 720includes, for example and without imputing limitation, department size,engagement, happiness, completion (e.g., survey completion, etc.), andaverage inter-department rating. Additionally, department informationsection 720 may include information for multiple time periods (e.g.,years, quarters, etc.) as well as an indication of a change ininformation, or delta, between the time periods.

FIG. 7B is an example department report interface 750 that includes datavisualizations for intuitive and fast review of department-specificinformation generated via surveys (e.g., as discussed above).Inter-departments ratings section 760 includes further visual elements(e.g., in comparison to department report interface 700) to indicateresponse strength and the like through, for example, a circle icon thatis sized according to a relationship between the particular departmentand the department listed for comparison. Further, departmentinformation section 770 includes a chart icon indicating that detailedinformation is available for a particular department statistic (e.g.,happiness, management, company leadership, compensation and benefits,workspace and tools, etc.). In some examples, the chart icon may beinteracted with to view an expanded graph view 780 which includes a barchart depicting a spread of responses related to a respective departmentstatistic.

FIG. 8 is an example reporting interface 800 for a user to review theirown ABIO score history as well as an ABIO composition of a respectiveteam. For example, reporting interface 800 includes an ABIO snapshot 802providing the user recent ratings information and a resultant ABIOscore. An ABIO history 804 provides comparison snapshots of the userABIO score over multiple time periods. Each comparison snapshot isdisplayed as a bar chart of each sub-score that makes up the ABIO scorefor the respective time period. As a result, a user can see changes tothe user ABIO score as well as quickly appraise along which dimensions(e.g., above, below, inside, outside, etc.) changes have taken place.Further, a team composition section 806 shows the user which employeetypes are present on a respective team and how many. The employee typesare based on respective ABIO scores for team members, which may be keptunknown to the user in order to maintain anonymity of the data.

FIG. 9 is an example team ABIO report interface 900 for reviewing ABIOinformation across an entire team for each member of the team. Anauthorized user (e.g., a team lead, manager, supervisor, etc.) canaccess team ABIO report interface 900 to review ABIO scores for allmembers of the team. Team ABIO report interface 900 can include atabular view 902 in which each row is associated with a particularemployee (e.g., team member) and columns provide identification 904,name 906, department 908, an overall ABIO value 910, and individual ABIOcomponent values 912-918.

More particularly, overall ABIO score 910 and individual ABIO componentsvalues 912-918 are further broken down to respective scores and samplesize used to determine said scores. Overall ABIO value 910 includes anoverall ABIO score 910A and respective overall ABIO sample size 910B,Above component value 912 includes an Above score 912A and respectiveAbove sample size 912B, Below component value 914 includes an Belowscore 914A and respective Below sample size 914B, Inside component value916 includes an Inside score 916A and respective Inside sample size916B, and Outside component value 918 includes an Outside score 918A andrespective Outside sample size 918B. As can be seen with Below score914A, where a sample size is insufficient to calculate a rating for anemployee (as discussed above), an associated value may be labeled as“insig” or the like to identify that value as uncalculated at the timedue to sample size limitations.

FIG. 10 is an example method 1000 that may be used to load and updateorg chart data to be used in the systems and methods discussed herein.In step 1002, the org chart data provided by the institution may beloaded. In some examples, the org chart data is provided by theinstitution in a tree type data structure.

In step 1004, the org chart data input is flattened and stored in thedatabase. In step 1006, survey data is loaded into the database andassociated with the org chart data. For example, the survey data mayinclude survey questions that are separated into different groups, whereeach group of questions is associated with a different level of the orgchart or a different branch of the org chart.

Once the initial org chart is loaded, it could be updated in thedatabase. To update the org chart, the institution may load an updatedorg chart in step 1008.

In step 1010, this updated org chart is flattened and compared to theorg chart currently stored in the database. In step 1012, the org chartstored in the database is updated to match the updated org chart data.

In step 1014, survey data is loaded into the database and associatedwith the updated org chart. The survey data may be the same as thesurvey data loaded in step 1006, or it may be different. Steps 1008 to1014 may be repeated for multiple updates.

FIG. 11 is an example system 1100. The example system 1100 comprises afront end 1120, a data store 1140, APIs 1150, and additional data likeorg chart 1104, person user 1106, and the survey raw data 1102.

The front end 1102 may be used to display data to users. The displayeddata may include an org chart with associated survey results 1122, thesurvey 1124, a home page 1126, a table report 1128, a team report 1130,a department report 1134, and a comment report 1136. The front end 1120may also be used to receive data input from the user. For example, theuser may input responses to the survey 1124 through the front end 1120.

The system 1100 also includes a data store 1140.The data store 1140 mayuse a cloud storage system, a storage device, or multiple storagedevices. The data store 1140 includes a survey store 1142 which storessurvey data to be displayed on the front end 1120, a person store 1144that stores user information and org chart data, and a division store1146 that stores data related to a division of a respective institution.

The system 1100 includes several different APIs. For example, survey API1152, person data endpoint 1154, division result API 1156, division data1158, and comments API 1160. The APIs provide an interface for thevarious parts of the system 1100 to communicate with each other. Forexample, once a user inputs survey 1124 results through the front end1120, the results are stored in survey store 1142.

Data from the survey store 1142 can be written into a database as surveyraw data 1102 through the survey API 1152. The APIs 1150 may also beused to retrieve data to be displayed on the front end. For example, theperson data API 1154 may be used to store user information 1106 andperson survey result 1108 in the person store 1144. The division resultAPI 1156 may be used to store institution result 1110 and division 1112in the division store 1146. The comments API 1160 may be used to displaycomments from the survey raw data 1102 to the comment report 1136 of thefront end 1120.

FIG. 12 is an example computing system 1200 that may implement varioussystems and methods discussed herein. The computer system 1200 includesone or more computing components in communication via a bus 1202. In oneimplementation, the computing system 1200 includes one or moreprocessors 1214. The processor 1214 can include one or more internallevels of cache 1216 and a bus controller or bus interface unit todirect interaction with the bus 1202. The processor 1214 mayspecifically implement the various methods discussed herein. Main memory1208 may include one or more memory cards and a control circuit (notdepicted), or other forms of removable memory, and may store varioussoftware applications including computer executable instructions, thatwhen run on the processor 1214, implement the methods and systems setout herein. Other forms of memory, such as a storage device 1210 and amass storage device 1212, may also be included and accessible, by theprocessor (or processors) 1214 via the bus 1202. The storage device 1210and mass storage device 1212 can each contain any or all of the methodsand systems discussed herein.

The computer system 1200 can further include a communications interface1218 by way of which the computer system 1200 can connect to networksand receive data useful in executing the methods and system set outherein as well as transmitting information to other devices. Thecomputer system 1200 can also include an input device 1206 by whichinformation is input. Input device 1206 can be a scanner, keyboard,and/or other input devices as will be apparent to a person of ordinaryskill in the art. The computer system 1200 can also include an outputdevice 1204 by which information can be output. Output device 1204 canbe a monitor, printer, USB, and/or other output devices or ports as willbe apparent to a person of ordinary skill in the art.

The system set forth in FIG. 12 is but one possible example of acomputer system that may employ or be configured in accordance withaspects of the present disclosure. It will be appreciated that othernon-transitory tangible computer-readable storage media storingcomputer-executable instructions for implementing the presentlydisclosed technology on a computing system may be utilized.

In the present disclosure, the methods disclosed may be implemented assets of instructions or software readable by a device. Further, it isunderstood that the specific order or hierarchy of steps in the methodsdisclosed are instances of example approaches. Based upon designpreferences, it is understood that the specific order or hierarchy ofsteps in the methods can be rearranged while remaining within thedisclosed subject matter. The accompanying method claims presentelements of the various steps in a sample order, and are not necessarilymeant to be limited to the specific order or hierarchy presented.

The described disclosure may be provided as a computer program product,or software, that may include a computer-readable storage medium havingstored thereon instructions, which may be used to program a computersystem (or other electronic devices) to perform a process according tothe present disclosure. A computer-readable storage medium includes anymechanism for storing information in a form (e.g., software, processingapplication) readable by a computer. The computer-readable storagemedium may include, but is not limited to, optical storage medium (e.g.,CD-ROM), magneto-optical storage medium, read only memory (ROM), randomaccess memory (RAM), erasable programmable memory (e.g., EPROM andEEPROM), flash memory, or other types of medium suitable for storingelectronic instructions.

Although the present technology has been described in detail for thepurpose of illustration based on what is currently considered to be themost practical and preferred implementations, it is to be understoodthat such detail is solely for that purpose and that the technology isnot limited to the disclosed implementations, but, on the contrary, isintended to cover modifications and equivalent arrangements that arewithin the spirit and scope of the appended claims. For example, it isto be understood that the present technology contemplates that, to theextent possible, one or more features of any implementation can becombined with one or more features of any other implementation.

What is claimed is:
 1. A method for determining employee sentimentratings, the method comprising: receiving ratings data, the ratings dataassociated with one or more employees and responsive to a survey;aggregating the ratings data to generate adjusted ratings for the one ormore employees; generating a report based on the generated adjustedratings; and generating a navigable interface comprising the generatedreport, the navigable interface accessible to an authorized user.
 2. Themethod of claim 1, further comprising: receiving an organizational (org)chart; visually associating one or more portions of the org chart withthe generated adjusted ratings; and wherein the generated navigableinterface further comprises the org chart.
 3. The method of claim 2,further comprising: receiving survey parameters, the survey parametersidentifying the one or more employees to survey; identifying a mismatchbetween the org chart and the identified one or more parameters, themismatch comprising one of an employee not included in the org chart oran employee of the org chart not included among the identified one ormore employees; and prompting the authorized user to specify a reasonfor the mismatch.
 4. The method of claim 1, further comprising:generating respective scores for each of the one or more employees, eachrespective score based on one or more of ratings received from coworkersorganizationally above a respective employee of the one or moreemployees, ratings received from coworkers organizationally below therespective employee, ratings received from coworkers within a shareddepartment of the respective employee, or ratings received fromcoworkers in different departments than that of the respective employee;and categorizing the one or more employees based on the respectivescores; wherein the navigable interface further comprises one of therespective scores or the categorized one or more employees.
 5. Themethod of claim 1, further comprising: grouping the adjusted ratingsdata into department groups; aggregating the grouped adjusted ratingsdata based on the department groups; and generating inter-departmentaldata based on the aggregated grouped adjusted ratings data, wherein thenavigable interface further comprises the inter-departmental data. 6.The method of claim 1, further comprising: generating a set of weightvalues for the one or more employees, the weight values corresponding tothe ratings data associated with the one or more employees; andgenerating the adjusted ratings by weighting the ratings data accordingto the set of weight values.
 7. The method of claim 1, furthercomprising: generating a projected performance for the one or moreemployees based on the adjusted ratings.
 8. A system for determiningemployee sentiment ratings, the system comprising: one or moreprocessors; and a memory comprising instructions for the one or moreprocessors to: receive ratings data, the ratings data associated withone or more employees and responsive to a survey; aggregate the ratingsdata to generate adjusted ratings for the one or more employees;generate a report based on the generated adjusted ratings; and generatea navigable interface comprising the generated report, the navigableinterface accessible to an authorized user.
 9. The system of claim 8,wherein the memory further comprises instructions to: receive anorganizational (org) chart; visually associate one or more portions ofthe org chart with the generated adjusted ratings; and wherein thegenerated navigable interface further comprises the org chart.
 10. Thesystem of claim 9, wherein the memory further comprises instructions to:receive survey parameters, the survey parameters identifying the one ormore employees to survey; identify a mismatch between the org chart andthe identified one or more parameters, the mismatch comprising one of anemployee not included in the org chart or an employee of the org chartnot included among the identified one or more employees; and prompt theauthorized user to specify a reason for the mismatch.
 11. The system ofclaim 8, wherein the memory further comprises instructions to: generaterespective scores for each of the one or more employees, each respectivescore based on one or more of ratings received from coworkersorganizationally above a respective employee of the one or moreemployees, ratings received from coworkers organizationally below therespective employee, ratings received from coworkers within a shareddepartment of the respective employee, or ratings received fromcoworkers in different departments than that of the respective employee;and categorize the one or more employees based on the respective scores;wherein the navigable interface further comprises one of the respectivescores or the categorized one or more employees.
 12. The system of claim8, wherein the memory further comprises instructions to: group theadjusted ratings data into department groups; aggregate the groupedadjusted ratings data based on the department groups; and generateinter-departmental data based on the aggregated grouped adjusted ratingsdata, wherein the navigable interface further comprises theinter-departmental data.
 13. The system of claim 8, wherein the memoryfurther comprises instructions to: generate a set of weight values forthe one or more employees, the weight values corresponding to theratings data associated with the one or more employees; and generate theadjusted ratings by weighting the ratings data according to the set ofweight values.
 14. The system of claim 8, wherein the memory furthercomprises instructions to: generate projected performance for the one ormore employees based on the adjusted ratings.
 15. A non-transitorycomputer readable medium storing instructions that, when executed by oneor processors, cause the one or more processors to: receive ratingsdata, the ratings data associated with one or more employees andresponsive to a survey; aggregate the ratings data to generate adjustedratings for the one or more employees; generate a report based on thegenerated adjusted ratings; and generate a navigable interfacecomprising the generated report, the navigable interface accessible toan authorized user.
 16. The non-transitory computer readable medium ofclaim 15, further storing instructions to: receive an organizational(org) chart; visually associate one or more portions of the org chartwith the generated adjusted ratings; and wherein the generated navigableinterface further comprises the org chart.
 17. The non-transitorycomputer readable medium of claim 16, further storing instructions to:receive survey parameters, the survey parameters identifying the one ormore employees to survey; identify a mismatch between the org chart andthe identified one or more parameters, the mismatch comprising one of anemployee not included in the org chart or an employee of the org chartnot included among the identified one or more employees; and prompt theauthorized user to specify a reason for the mismatch.
 18. Thenon-transitory computer readable medium of claim 15, further storinginstructions to: generate respective scores for each of the one or moreemployees, each respective score based on one or more of ratingsreceived from coworkers organizationally above a respective employee ofthe one or more employees, ratings received from coworkersorganizationally below the respective employee, ratings received fromcoworkers within a shared department of the respective employee, orratings received from coworkers in different departments than that ofthe respective employee; and categorize the one or more employees basedon the respective scores; wherein the navigable interface furthercomprises one of the respective scores or the categorized one or moreemployees.
 19. The non-transitory computer readable medium of claim 15,further storing instructions to: group the adjusted ratings data intodepartment groups; aggregate the grouped adjusted ratings data based onthe department groups; and generate inter-departmental data based on theaggregated grouped adjusted ratings data; wherein the navigableinterface further comprises the inter-departmental data.
 20. Thenon-transitory computer readable medium of claim 15, further storinginstructions to: generate a set of weight values for the one or moreemployees, the weight values corresponding to the ratings dataassociated with the one or more employees; generate the adjusted ratingsby weighting the ratings data according to the set of weight values; andgenerate a projected performance for the one or more employees based onthe adjusted ratings.